E-nose: A low-cost fruit ripeness monitoring system

IF 2.4 4区 农林科学 Q2 AGRICULTURAL ENGINEERING Journal of Agricultural Engineering Pub Date : 2022-11-03 DOI:10.4081/jae.2022.1389
Pankaj Tyagi, R. Semwal, Anju Sharma, U. Tiwary, P. Varadwaj
{"title":"E-nose: A low-cost fruit ripeness monitoring system","authors":"Pankaj Tyagi, R. Semwal, Anju Sharma, U. Tiwary, P. Varadwaj","doi":"10.4081/jae.2022.1389","DOIUrl":null,"url":null,"abstract":"All fruits emit some specific volatile organic compounds (VOCs) during their life cycle. These VOCs have specific characteristics, by using these characteristics fruit ripening stage can be identified without destructing the fruit. \nIn this study, an application-specific electronic nose device was designed for monitoring fruit ripeness.The proposed electronic nose is cost-efficient and does not require any modern or costly laboratory instruments. Metal oxide semiconductor (MOS) sensors were used for designing the proposed electronic nose. These MOS sensors were integrated with a microcontroller board to detect and extract the meaningful features of VOCs, and an artificial neural network (ANN) algorithm was used for pattern recognition. Measurements were done with apples, bananas, oranges, grapes, and pomegranates. The designed electronic nose proved to be reliable in classifying fruit samples into three different fruit ripening stage (unripe, ripe, and over-ripe) with high precision and recall. The proposed electronic nose performed uniformly on all three fruit ripening stages with an average accuracy of ≥ 95%.","PeriodicalId":48507,"journal":{"name":"Journal of Agricultural Engineering","volume":"34 1 1","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2022-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Agricultural Engineering","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.4081/jae.2022.1389","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"AGRICULTURAL ENGINEERING","Score":null,"Total":0}
引用次数: 5

Abstract

All fruits emit some specific volatile organic compounds (VOCs) during their life cycle. These VOCs have specific characteristics, by using these characteristics fruit ripening stage can be identified without destructing the fruit. In this study, an application-specific electronic nose device was designed for monitoring fruit ripeness.The proposed electronic nose is cost-efficient and does not require any modern or costly laboratory instruments. Metal oxide semiconductor (MOS) sensors were used for designing the proposed electronic nose. These MOS sensors were integrated with a microcontroller board to detect and extract the meaningful features of VOCs, and an artificial neural network (ANN) algorithm was used for pattern recognition. Measurements were done with apples, bananas, oranges, grapes, and pomegranates. The designed electronic nose proved to be reliable in classifying fruit samples into three different fruit ripening stage (unripe, ripe, and over-ripe) with high precision and recall. The proposed electronic nose performed uniformly on all three fruit ripening stages with an average accuracy of ≥ 95%.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
电子鼻:一种低成本的水果成熟度监测系统
所有水果在其生命周期中都会释放出一些特定的挥发性有机化合物(VOCs)。这些挥发性有机化合物具有特定的特征,利用这些特征可以在不破坏果实的情况下识别果实的成熟阶段。本研究设计了一种用于监测水果成熟度的专用电子鼻装置。所提出的电子鼻具有成本效益,不需要任何现代化或昂贵的实验室仪器。采用金属氧化物半导体(MOS)传感器设计电子鼻。这些MOS传感器与微控制器板集成,用于检测和提取voc的有意义特征,并使用人工神经网络(ANN)算法进行模式识别。测量对象包括苹果、香蕉、橙子、葡萄和石榴。实验证明,所设计的电子鼻能够可靠地将水果样品分为三个不同的成熟阶段(未成熟、成熟和过熟),具有较高的准确率和召回率。建议的电子鼻在所有三个水果成熟阶段表现均匀,平均准确率≥95%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Journal of Agricultural Engineering
Journal of Agricultural Engineering AGRICULTURAL ENGINEERING-
CiteScore
2.30
自引率
5.60%
发文量
40
审稿时长
10 weeks
期刊介绍: The Journal of Agricultural Engineering (JAE) is the official journal of the Italian Society of Agricultural Engineering supported by University of Bologna, Italy. The subject matter covers a complete and interdisciplinary range of research in engineering for agriculture and biosystems.
期刊最新文献
Comparison of two different artificial neural network models for prediction of soil penetration resistance Apple recognition and picking sequence planning for harvesting robot in the complex environment Monitoring and multi-scenario simulation of agricultural land changes using Landsat imageries and FLUS model on coastal Alanya Variable-rate spray system for unmanned aerial applications using lag compensation algorithm and pulse width modulation spray technology Comparative analysis of 2D and 3D vineyard yield prediction system using artificial intelligence
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1